SAN FRANCISCO, CA: Findify, an e-commerce search solution powered by machine learning and Big Data, has chosen Databricks, a provider of cloud-based integrated workspace for Big Data, as its Big Data platform to use Spark for its mission-critical use cases containing extract, transform, and load (ETL), analytics and machine learning.

“Everything that Findify does is data-driven, from choosing which features to develop, to exposing the right analytics to their customers. Databricks is helping to further Findify’s mission of creating frictionless online shopping experiences, while enabling their team to gain significant productivity improvements and easily collaborate across the globe,” says Ali Ghodsi, CEO, Databricks.

By using Databricks platform, Findify aims to improve the operation of complicated machine learning models and simplify complex Big Data operations. The advantages that Findify gets from Databricks include: faster time to complete projects where zero maintenance Spark clusters and Jobs infrastructure leads to faster feature development and diminished customer frustration; more efficient operations—the controlled platform removes the time spent on DevOps and infrastructure issues, enabling the engineering team to focus on leveraging machine learning to build innovative features.

Enhanced collaboration is another advantage that Findify gets where it enables the easy iteration, visualization and collaboration enabling efficient and faster completion of projects. In addition, the Databricks platform also allows Findify to concentrate less on DevOps and more on employing enhanced machine learning algorithms and models to develop innovative features, while designing new revenue opportunities for customers.